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ABSTRACT: Objective
Identify metabolic changes produced by dimethyl fumarate (DMF) treatment and link them to immunological effects.Methods
We enrolled 18 MS patients and obtained blood prior to DMF and 6 months postinitiation. We also enrolled 18 healthy controls for comparison. We performed global metabolomics on plasma and used weighted correlation network analysis (WGCNA) to identify modules of correlated metabolites. We identified modules that changed with treatment, followed by targeted metabolomics to corroborate changes identified in global analyses. We correlated changes in metabolite modules and individual metabolites with changes in immunological parameters.Results
We identified alterations in lipid metabolism after DMF treatment - increases in two modules (phospholipids, lysophospholipids and plasmalogens) and reduction in one module (saturated and poly-unsaturated fatty acids) eigen-metabolite values (all P < 0.05). Change in the fatty acid module was greater in participants who developed lymphopenia and was strongly associated with both reduction in absolute lymphocyte counts (r = 0.65; P = 0.005) and change in CD8+ T cell subsets. We also noted significant correlation of change in lymphocyte counts with multiple fatty acid levels (measured by targeted or untargeted methods).Interpretation
This study demonstrates that DMF treatment alters lipid metabolism and that changes in fatty acid levels are related to DMF-induced immunological changes.
SUBMITTER: Bhargava P
PROVIDER: S-EPMC6331509 | biostudies-literature | 2019 Jan
REPOSITORIES: biostudies-literature
Bhargava Pavan P Fitzgerald Kathryn C KC Venkata Swarajya L V SLV Smith Matthew D MD Kornberg Michael D MD Mowry Ellen M EM Haughey Norman J NJ Calabresi Peter A PA
Annals of clinical and translational neurology 20181030 1
<h4>Objective</h4>Identify metabolic changes produced by dimethyl fumarate (DMF) treatment and link them to immunological effects.<h4>Methods</h4>We enrolled 18 MS patients and obtained blood prior to DMF and 6 months postinitiation. We also enrolled 18 healthy controls for comparison. We performed global metabolomics on plasma and used weighted correlation network analysis (WGCNA) to identify modules of correlated metabolites. We identified modules that changed with treatment, followed by targe ...[more]